How To Building and Running Llama 3.2 1B Instruct with Qualcomm AI Engine Direct Backend？

Right Case

When I follow the doc : https://github.com/pytorch/executorch/blob/main/examples/models/llama/README.md#enablement,
I export the Llama3.2-1B-Instruct:int4-spinquant-eo8 model to xnnpack backend pte successfully, and working alright on cpu.

Bad Case

But as the link: https://github.com/pytorch/executorch/blob/main/examples/models/llama/README.md, when I export to the qnn backend using mode Llama3.2-1B-Instruct, I can get the out pte file, but when I make it running on the android device, it not working right.

I export pte file like this:

python -m examples.models.llama.export_llama --checkpoint "${MODEL_DIR}/consolidated.00.pth" -p "${MODEL_DIR}/params.json" -kv --disable_dynamic_shape --qnn --pt2e_quantize qnn_16a4w -d fp32 --metadata '{"get_bos_id":128000, "get_eos_ids":[128009, 128001]}' --soc_model SM8550 --output_name="llama3_2_ptq_qnn_.pte"

This is the part of output when I export

INFO:executorch.backends.qualcomm.qnn_preprocess:Visiting: aten_permute_copy_default_979, aten.permute_copy.default
INFO:executorch.backends.qualcomm.qnn_preprocess:Visiting: aten_squeeze_copy_dims_175, aten.squeeze_copy.dims
INFO:executorch.backends.qualcomm.qnn_preprocess:Visiting: aten_add_tensor_79, aten.add.Tensor
INFO:executorch.backends.qualcomm.qnn_preprocess:Visiting: aten_select_copy_int_512, aten.select_copy.int
INFO:executorch.backends.qualcomm.qnn_preprocess:Visiting: aten_rms_norm_default_32, aten.rms_norm.default
INFO:executorch.backends.qualcomm.qnn_preprocess:Visiting: aten_view_copy_default_288, aten.view_copy.default
INFO:executorch.backends.qualcomm.qnn_preprocess:Visiting: aten_permute_copy_default_980, aten.permute_copy.default
INFO:executorch.backends.qualcomm.qnn_preprocess:Visiting: aten_convolution_default_112, aten.convolution.default
INFO:executorch.backends.qualcomm.qnn_preprocess:Visiting: aten_permute_copy_default_981, aten.permute_copy.default
INFO:executorch.backends.qualcomm.qnn_preprocess:Visiting: aten_view_copy_default_289, aten.view_copy.default
INFO:executorch.backends.qualcomm.qnn_preprocess:Visiting: quantized_decomposed_dequantize_per_tensor_tensor, quantized_decomposed.dequantize_per_tensor.tensor
[INFO] [Qnn ExecuTorch]: Destroy Qnn backend parameters
[INFO] [Qnn ExecuTorch]: Destroy Qnn context
[INFO] [Qnn ExecuTorch]: Destroy Qnn device
[INFO] [Qnn ExecuTorch]: Destroy Qnn backend
/home/hebaotong/AI/Executorch/executorch_new/executorch/exir/emit/emitter.py:1512: UserWarning: Mutation on a buffer in the model is detected. ExecuTorch assumes buffers that are mutated in the graph have a meaningless initial state, only the shape and dtype will be serialized.
warnings.warn(
INFO:root:Required memory for activation in bytes: [0, 17552384]
modelname: llama3_2_ptq_qnn
output_file: llama3_2_ptq_qnn_.pte
INFO:root:Saved exported program to llama3_2_ptq_qnn_.pte

Screenshot of run status

Start with examples/models/llama/README.md, especially the QNN export instructions and the provided export command. Compare the successful XNNPACK path with the Android run shown in the issue, then identify the missing runtime failure details; done means the QNN-exported Llama 3.2 1B model runs correctly on the Android device.